Image Noise Reduction
Remove noise and grain from your photos. Choose from median, gaussian, or bilateral filtering with adjustable strength and before/after preview.
Drop images here or click to browse
Supports JPG, PNG, WebP. Multiple files supported.
All processing happens in your browser. Your images never leave your device.
How to Reduce Image Noise
Upload Image
Drag and drop or click to upload one or more noisy images.
Choose Filter
Select a filtering method and adjust the strength. Compare before and after in the preview.
Download Result
Download the denoised image in high quality. Batch processing supported.
Use Cases
Low Light Photos
Clean up grainy photos taken in low light or high ISO settings for clearer results.
Scanned Documents
Remove scanner noise and artifacts from digitized documents and old photographs.
Old Photo Restoration
Remove grain and artifacts from vintage or deteriorated photographs to restore clarity.
Medical Imaging
Reduce noise in medical scans and X-rays to improve diagnostic clarity and readability.
Surveillance Footage
Clean up noisy security camera stills for better subject identification and evidence quality.
Astrophotography
Remove sensor noise from long-exposure night sky photos to reveal cleaner star fields and nebulae.
Frequently Asked Questions
Which filter method should I use?
Median filter is best for salt-and-pepper noise. Gaussian filter smooths overall noise evenly. Bilateral filter reduces noise while preserving edges, making it ideal for photographs.
Will noise reduction affect image quality?
Noise reduction involves a trade-off between noise removal and detail preservation. Start with a low strength and increase gradually. Use bilateral filtering with preserve details enabled for the best balance.
What is the difference between median and bilateral filtering?
Median filtering replaces each pixel with the median of its neighbors, excellent for salt-and-pepper noise. Bilateral filtering considers both spatial distance and color similarity, preserving edges while smoothing noise.
Can noise reduction recover lost details?
Noise reduction removes random pixel variation but cannot recover details lost during capture. It works best when the original signal is present but obscured by noise. Use moderate strength to avoid over-smoothing.
When should I use noise reduction vs. sharpening?
Apply noise reduction first to remove grain, then sharpen to restore edge clarity. Sharpening a noisy image amplifies the noise. The correct order is: denoise, then sharpen for optimal results.
Ready to Reduce Noise?
Upload your noisy image and get a cleaner result in seconds. Free, fast, and private.